Analyzing the performance of different fuzzy measures with generalizations of the Choquet integral in classification problems

Fuzzy Rule Based Classification Systems are an useful tool to deal with classification problems. In these systems, one fundamental point is the manner of how the available information about the problem is aggregated. The mechanism responsible to perform the aggregation is the Fuzzy Reasoning Method (FRM). Recently, some FRMs using generalizations of the Choquet integral to perform the aggregation were proposed in the literature. Since these generalizations are defined considering a specific fuzzy measure, in this paper we apply different fuzzy measures in the generalizations that presented the best performance in each study in the literature. We analyze how the performance is affected according to each fuzzy measure.